This application relates to techniques for estimating motion and applications of such techniques in various applications including imaging applications such as magnetic resonance imaging (MRI), positron emission tomography (PET) imaging, computed tomography (CT) imaging, and ultrasound imaging.
Imaging through MRI techniques is well known and has been widely applied in imaging applications in medical, biological and other fields. An MRI system produces an image of a sample or a selected body part of a subject (e.g., a person or an animal) under examination by manipulating the magnetic spins in the body part and processing measured responses from the magnetic spins. In some implementations, an MRI system may include hardware to generate different magnetic fields for imaging, including a static magnetic field along a z-direction to polarize the magnetic spins, gradient fields along mutually orthogonal x, y, or z directions to spatially select a body part for imaging, and an RF magnetic field to manipulate the spins.
When the sample or the subject under imaging moves, the obtained MRI images may exhibit motion artifacts that degrade the images. The nature of the motion artifact depends upon when the subject or sample moves during the MRI pulse sequence. Motion artifacts can be caused by various sources, including mechanical vibrations of the subject or sample. Such motion artifacts can be problematic when imaging a living subject such as a person or an animal because physiological effects such as involuntary motion, cardiac pulsations, blood flow, respiration, and eye movements may lead to large motion artifacts. Physical restraints of the subject may help immobilize the subject during scan acquisition, but these restraints are generally difficult to use, uncomfortable for the subject, and cannot fully prevent motion artifact in these data. Hence, there is a need to reduce the motion artifacts in MRI images.
Various techniques have been developed to correct for motion artifacts in MRI, such as retrospective motion correction techniques and prospective motion correction techniques. Retrospective motion correction techniques correct for motion artifact after the data have been collected using post processing techniques. Implementations of retrospective motion correction techniques have various limitations in removing motion artifact. For example, it can be difficult for various retrospective correction techniques to correct for the motion-induced changes in the spin excitation history (spin history effects) or motion artifacts caused by motion that occurs during the scan itself (e.g. intra-scan motion); some retrospective motion correction techniques can introduce blurring in the images because the images are resampled into a common spatial coordinate system.
Prospective motion correction techniques correct for motion artifact during the scan process and thus are generally considered superior at correcting for motion artifact when compared to retrospective motion correction techniques. In implementation, the motion of the sample is tracked or estimated sequentially in time during the scan acquisition period. One method for tracking the motion of the sample or subject during the scan acquisition is to use navigator scans or navigator echoes. Prospective motion correction techniques which use navigator echoes for motion tracking are generally referred to as navigated MRI sequences. There are many different types of navigator echoes depending upon how the navigator echoes are collected and there are many different techniques to estimate motion from the navigator echoes. Some common types of navigator echoes include orbital navigator echoes, cloverleaf navigator echoes, spherical navigator echoes, and spiral navigator echoes. Typically, the navigator echoes only acquire data in a small portion of k-space and therefore the limited amount of information about the sample or subject contained in these navigator echoes makes accurate and rapid estimation of the motion of the sample or subject difficult. Multiple navigator echoes can be repeated one after another so that a more accurate estimate of the motion can be obtained.
Some other examples of prospective motion correction techniques of MRI data include tracking fiducial markers which are visible in the MR image and optical tracking of reflectors fixed to the subject. Self-navigating MRI sequences can also be used to estimate motion of the sample from the acquired MRI data for prospective motion correction of MRI data.